class_docstr: An experimental 'lightweight' variant that sums avg_pool and max_pool results.
      
code: def __init__(self, kernel_size=7, gate_layer="sigmoid"):
      super(LightSpatialAttn, self).__init__()
      self.conv = ConvNormAct(1, 1, kernel_size, apply_act=False)
      self.gate = create_act_layer(gate_layer)
  
imports: import torch
  from torch import nn
  import torch.nn.functional
  from .conv_bn_act import ConvNormAct
  from .create_act import create_act_layer, get_act_layer
  from .helpers import make_divisible
label_desc: Use image node_id 1 to create a new LightSpatialAttn object from inherited base classes: nn with example: obj = LightSpatialAttn(kernel_size, gate_layer)